Project carried out by: Joanna Grebosz, Prof Mike Larkin, Dr Chris Allen, Dr Leonid Kulakov QUB, School of Biological Sciences

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1 Project carried out by: Joanna Grebosz, Prof Mike Larkin, Dr Chris Allen, Dr Leonid Kulakov QUB, School of Biological Sciences

2 Marie Curie s homeland Molecular Biotechnologist (MSc in University of Warmia and Mazury in Olsztyn) Master s thesis title: Changes in the roots proteome of Triticosecale grains germinating under osmotic stress conditions

3 Consists mostly of methane Renewable energy, heat production or vehicle fuel Environmental friendly, economically beneficial Compound Content Methane 48-65% CO % N 2 <1-17% O 2 <1% Volatile organic compounds 5-268mg/m 3 H 2 1-5% H 2 S 0-3%

4 Reactor Anaerobic digestion process of the feedstock carried out by the microbial community Methane yield depends on the feedstock Liquid Animal manure Sewage sludge Food waste Solid Food waste Agricultural waste Organic municipal waste

5 Hydrolysis Key cellulolytic bacteria: Cellulomonas, Clostridium, Bacillus, Thermomonospora, Ruminococcus, Baceriodes, Erwinia, Acetovibrio, Microbispora or Streptomyces Acidogenesis ( (fermentation) Bacteria: Acetobacterium, Clostridium, Sporomusa, Saccharomyces, Butyribacterium, Lactobacillus, Streptococcus Acetogenesis Homoacetogenic bacteria: Acetobacterium (for example Acetobacterium woodii), Sporomusa Other bacteria: Clostridium (for example Clostridium aceticum),ruminococcus and Eubacterium Methanogenesis Production of methane by methanogens (Archaea) Some known aceticlastic Archaea: Methanosaeta, Methanosarcina Hydrogenotrophic Archaea: Methanomicrobiales (Methanoculleus)

6 Methanogens Aceticlastic Hydrogenotrophic Methanomicrobia Methanobacteria Methanococci Methanomicrobia Methanosarcinales Methanomicrobiales Methanosarcina sp. Methanosaeta sp. Methanoculleus sp.

7 Feedstock Polymers (lipids, polysaccharides, proteins) Hydrolysis (Clostridia etc.) Ammonia Acetogenesis (Acetobacterium woodii etc.) Mono- and oligomers (long chain fatty acids, sugars, amino acids) Acidogenesis (Acetobacterium, Clostridium, OD1 etc.) Volatile fatty acids H 2 S H 2 Acetate Methanogenesis (Methanosaeta, Methanomicrobiales) Short-chain VFA (eg. propionate) Biogas mostly methane H 2 and CO 2

8 The possible OD1 and hydrogenotrophic methanogens relationship investigation by using metagenomic tools Significance of the relationship for methane yield Defining the optimal hydrolysis conditions by OD1 numbers and microbial shifts investigation

9 Sample from mesophilic two-stage anaerobic digester (feedstock slurry) DNA extraction PowerSoil DNA Isolation Kit (Mo Bio Laboratories) or Griffiths et al. (2000) method qpcr or PCR and 454-pyrosequencing, especially for OD1 and methanogenic community investigations Use of general 16S primers or primers for some functional genes (for example for mcra Archaea gene) in PCR or qpcr Laboratory-scale digesters Control and treatment digesters to test hypotheses and optimise hydrolysis for biogas production Inoculation from two-stage digester above

10 DNA concentration after extraction (PowerSoil DNA Isolation Kit) 7ng/µl and 51 ng/µl PCR with general bacterial 16S primers: 63f and 1387f failure at the beginning (due to the inhibitors presence), after optimisation - success The need to choose the most optimal extraction method A B Fig. 1. The electrophoregrams obtained by using the extracted DNA (A) and the amplification products after PCR with 63f and 1387r primers (B). Designation: 1 and 2 DNA isolated from the anaerobic digester s samples, 3 DNA isolated from the soil sample for comparison purposes, 4-1kb molecular mass marker, 4, 5 and 6 the anaerobic digester s samples amplicons, 7 bacterial positive control Fig. 2. The electrophoregram obtained after PCR with 63f and 1387r primers by using the extracted and diluted DNA. Designation: 1 and 2 mass markers, PCR products using the following dilutions of DNA template: 3 1:5 dilution, 4 1:10 dilution, 5 1:20 dilution, 6 1:50 dilution, 7 1:100 dilution, 8 positive control

11 OD1 presence can be connected with the dominance of hydrogenotrophic methanogens that bring low methane yield OD1 biomarker of low methane yields that can be investigated by robust metagenomic tools OD1 analysis hydrolysis optimisation (by use of different feedstocks) low OD1 numbers and high methane yield The project the connection between specific microbial shifts and biogas production efficiency by using more robust metagenomic techniques

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